Evidence map›Paper›PMID 36330432›Full record

ArticleFrontiers in neurology2022

Identification of mRNA expression biomarkers associated with epilepsy and response to valproate with co-expression analysis.

Jun Min, Qinglan Chen, Wenyue Wu, Jing Zhao, Xinming Luo

Abstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jun MinDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Qinglan ChenDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Wenyue WuDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jing ZhaoDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Xinming LuoDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Valproate (VPA) resistance was reported to be an important predictor of intractable epilepsy. We conducted this study to identify candidate biomarkers in peripheral blood correlated with VPA resistance. Methods: The microarray dataset (GSE143272) was downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed to construct co-expression modules and obtain the most prominent module associated with VPA resistance. Differentially expressed genes (DEGs) between VPA-responsive and VPA-resistant patients were obtained using the "Limma" package in R. The intersections between the most prominent module and DEGs were identified as target genes. Metascape was performed to discover the possible involved pathways of the target genes. GeneCards database was used to know the function of each target gene. Results: All genes in the GSE143272 were divided into 24 different modules. Among these modules, the darkred module showed a pivotal correlation with VPA resistance. A total of 70 DEGs between VPA-responsive and VPA-resistant patients were identified. After taking the intersection, 25 target genes were obtained. The 25 target genes were significantly enriched in T cell receptor recognition, T cell receptor signaling pathway, regulation of T cell activation, cytokine-cytokine receptor interaction, and Conclusion: We identified 25 target genes prominently associated with VPA resistance, which could be potential candidate biomarkers for epilepsy resistance in peripheral blood. The peripheral blood T cells may play a crucial role in VPA resistance. Those genes and pathways might become therapeutic targets with clinical usefulness in the future.

Indexed as

biomarkerdrug resistanceepilepsyT cellsvalproateWGCNA

Identifiers

PMID36330432
PMCPMC9624511

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